• DocumentCode
    2957131
  • Title

    Analog integrated circuit parameter fault diagnosis using artificial neural network

  • Author

    Jingfan Zhang ; Junren Gan ; Linsheng Yao

  • Author_Institution
    Inst. of Metall., Acad. Sinica, Shanghai
  • fYear
    1996
  • fDate
    21-24 Oct 1996
  • Firstpage
    400
  • Lastpage
    403
  • Abstract
    An artificial neural network method used for analog IC parameter fault diagnosis is presented in this paper. It is fast and accurate. Therefore it has boundless prospects in the field of analog IC parameter fault diagnosis. With the rapid development in IC technology, the fault diagnosis problem of analog IC has become more acute. The traditional methods´ computation complexity and inaccuracy of results make most of them still unacceptable. We therefore research and develop an artificial neural network system to resolving the low velocity and low measurability problem of the traditional methods
  • Keywords
    analogue integrated circuits; fault diagnosis; integrated circuit testing; network parameters; neural nets; analog integrated circuit parameter fault diagnosis; artificial neural network; Analog integrated circuits; Artificial neural networks; Backpropagation algorithms; Circuit simulation; Circuit testing; Computer networks; Fault diagnosis; Linear circuits; Neural networks; Reflection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ASIC, 1996., 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    7-5439-0940-5
  • Type

    conf

  • DOI
    10.1109/ICASIC.1996.562837
  • Filename
    562837